Online advertisements are important revenue generators for publishers. As consumers turn away from traditional media to spend more time on the Internet, and increase spending there as well, online advertisements are becoming even more critical. One key concern for marketers is how to effectively target online advertisements to consumers that are interested and likely to buy the specific or even uniquely identifiable product or service, or even inquire or pay attention to the pitch.
When a marketer configures a marketing campaign to a server, a PPC value is assigned to advertisements to entice publishers to prominently display the advertisements amongst other published content. However, a marketer may not know what PPC values (or other values drawn from user interaction) to start out with. Also, a marketer can have an overall budget that needs to be allocated among several advertisements. An inefficiently configured marketing campaign is likely not an effective one.
What is needed is a technique for steering distributions for connections for campaigns of uniquely identifiable objects (UIOs) based on predicted distributions. The technique should also update initial weightings dynamically in response to actual connection data as it comes available.